Layers and the Future of Data and Analytics in Business

Pitney Bowes


It took geologists over 250 years to go from the simple idea that the mapping stratigraphy (exposed rock formations sometimes referred to as “layer cake” geology), could reveal Earth’s fantastic history. But it wasn’t until radioactive isotopes, high-precision instruments, were used that we understood the absolute age and mineral composition to create a timeline under which the Earth took shape.

In business, data is everywhere. Mobile data, in particular could be described as the “sediment” that contributes to the formation of our modern digital age. As with geological layers, or strata, the combination of myriad data can tell a more comprehensive story — one that includes a multi-dimensional perspective of place, time and people. Once data is combined, each set positioned relative to and juxtaposed with each other, data becomes more than just a resource; it becomes a value, an asset, a fuel that can power insight, drive revenue and refine a customer’s experience.

Why Layers Matter

For nearly 100 years, Pitney Bowes has worked to develop those tools and perspectives. We’ve organized the data around us to understand how addresses connect and bind people, places, and things together. Addresses act as a pivot point for layers of data, converting raw information into a near real-time history of consumer demands, resulting in “impulse” buying at the point of sale.

Fundamentally, data is a layering problem. Every aspect of an address involves a host of variables: physical locations, structures and the materials of which they’re made; the people associated with it in the present and past; tax codes, school districts, zoning, weather, topography, and more. If the proximity of these data and attributes are used effectively, the impact is significant: property is taxed effectively; school districts will balance the educational needs of the citizenry; and economic development thrives.

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Data layers. Image: Layers of WHERE, Pitney Bowes.
Data layers. Image: The Layers of WHERE, Pitney Bowes.

Pitney Bowes recognized their century of knowledge about how addresses worked to become a provider of a broader portfolio of data. We invested in aggregating, validating, building, and packaging these data with the goal of identifying and capturing the changes of an emerging digital economy, and simplifying the process for our customers to acquire and ingest the data, and then building fit-for-purpose products as quickly as possible.

What’s in a Layer?

Today, most data are associated with a geographic location, especially mobile data, which by default contains a latitude and longitude. Every item bought at a physical retail location, every purchase made on Amazon, and every post to Facebook carries a location. The result is layer after layer of data, and the capability to visualize the proximity of each layer provides insights not found in any spreadsheet. These insights help the retailers better merchandize stores and deliver the right products, at the right time, to the right consumer.

In government, urban planners work to optimize the best route for a new interstate, which requires information garnered from layers of data, including environment (the highway should avoid remediation, wetlands, etc.), geologic (the highway must be bedrock), hydrology (establishing proper drainage and runoff), and existing infrastructure (the highway should be routed around historically significant locations/buildings, like cemeteries or landmarks, for example). Alone, each of these layers provide an insight. Together, they provide the blueprint from which we can construct a multi-million-dollar highway.

The Future of Layers

Indeed, the future of data and analytics in business isn’t just accumulating more data. The future consists of high quality data, optimizing storage and developing the right analytical tools that give managers a means to craft better decisions.

For example, insurance companies must comprehend the risks and perils of certain geographic regions so they can effectively save money through more efficient underwriting. Today, more variables that impact the pricing of policies can now be modeled because of advanced computing resources, precise location-based information, and authoritative data.

Telecommunications companies are always seeking to provide better coverage, especially when planning the rollout of a new product or service, such as 5G. To determine the needs of the local market, wireless providers are looking for population centers with multiple transmitters. The more transmitters there are in a given area, the shorter the wavelength, and higher the frequency—and the better the signal. But in addition to transmitters, the telecom companies need to determine the location and extent of the target market.

Here, layering of data make a lot of sense. Population data, cell tower locations, commercial business addresses and the expendable income of consumers tells a complete story. It’s only with the right mix of data that huge investments of telecommunication infrastructure can be justified.

There is raw data everywhere, after all, from traffic lights to cell phone transmissions. All of these attributes have value if layered properly, but often companies don’t have enough information to know what layers to stack, and what algorithms to deploy to yield real insight and knowledge.

Companies need to take advantage of the years of expertise data professionals have turning address verification, validation, and standardization into actionable insight. We know, for example, that much of the data we collect is fluid. Street names change as populations grow and shrink—Walnut Street may become West Walnut Street; and First Avenue may become the name of a city’s retired mayor. Other locations can sit at multiple addresses—buildings themselves can and do often have multiple addresses—even zip codes change periodically. In addition, multiple buildings may share one address, or one address may accommodate multiple delivery points. If the data vendor isn’t tracking and coordinating these changes, then too much of the logistical work falls on the company trying to benefit from the information, and interferes with an accurate understanding of the commercial strata.

As location technology becomes more commonplace, democratizing spatial data, and making it accessible to every business profession will be critical to future business planning. That means organizations can build a business case to do things they’ve never done before because it’s too difficult, it’s cost-prohibitive, and/or the computing power was just not available. Today, Pitney Bowes has foreseen these changes and the results are revolutionary.

About the Author

Joe Francica is currently Managing Director, Geospatial Industry Solutions for Pitney Bowes. He is recognized as one most influential people in geospatial technology and the leading proponent of location intelligence (LI) solutions for over 30 years, having founded the Location Intelligence Conference in 2004. Francica has published and broadcast over 500 articles and podcasts on LI and has contributed to three books: Profiting from a GIS (published in 1993 by GIS World Books; edited by G. Castle), Geographic Information Systems in Business (published in 2005 by Idea Group Publishing; edited by J. Pick), and the Encyclopedia of GIS (published by Springer).

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